Average idiosyncratic volatility and firm idiosyncratic volatility increase with the number of listed firms. Average industry idiosyncratic volatility increases with the number of listed firms in the industry. We ex-plain the relation between idiosyncratic volatility and the number of listed...

We explore the effects of physical and regulatory risks related to biodiversity loss on economic activity and asset values. We first develop a news-based measure of aggregate biodiversity risk and analyze how it varies over time. We also construct and publicly release several firm-level measures...

We propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of...

A war-related factor model derived from textual analysis of media news reports explains the cross section of expected asset returns. Using a semi-supervised topic model to extract discourse topics from 7,000,000 New York Times stories spanning 160 years, the war factor predicts the cross section...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We survey the growing literature emphasizing the role that supply-and-demand forces play in shaping the term structure of interest rates. Our starting point is the Vayanos and Vila (2009, 2021) model of the term structure of default-free bond yields, which we present in both discrete and...

General Partners (GPs) in private equity face a trade-off between focusing their skills and effort on fewer investments to earn higher returns, or investing more broadly to reduce risk through diversification. Using a novel, deal-level dataset of 5,925 global investments from 1999 to 2016, we...

We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

Using a semi-supervised topic model on 7,000,000 New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock and bond market returns to test rational and behavioral hypotheses about market valuation of disaster risk. Focusing on media discourse...

We characterize how risk evolves during a crisis. Using high-frequency data, we find that the first two principal components (PCs) of the covariance matrix of global asset returns experience large, sudden, and temporary spikes coinciding with well-known crises - Covid-19 pandemic, Global...